Decision theory, reinforcement learning, and the brain

P. Dayan, N. D. Daw
2008 Cognitive, Affective, & Behavioral Neuroscience  
Decision theory is a core competence for animals and humans acting and surviving in environments they only partially comprehend, gaining rewards and punishments for their troubles. Decision theoretic concepts permeate experiments and computational models in ethology, psychology and neuroscience. Here, we review a well known, coherent Bayesian approach to decision-making, showing how it unifies issues in Markovian decision problems, signal detection psychophysics, sequential sampling and optimal
more » ... exploration, and discuss paradigmatic psychological and neural examples of each problem. We discuss computational issues concerning what subjects know about their task, and how ambitious they are in seeking optimal solutions; algorithmic topics addressing model-based and model-free methods for making choices; and highlight key aspects of the neural implementation of decision-making.
doi:10.3758/cabn.8.4.429 pmid:19033240 fatcat:6l37gqtenfg3xonzfdd3kuk3sy